Session: Sensors for Water Analysis 4.0: Analytics Meets Digitization

Session Chair: Dr. Günther Proll
English

Plasmonic sensor as on-site data source for the monitoring of environmental pollutants

Dr. Christiane Schuster, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung
Miniaturized sensor concepts for cost-efficient and continuous on-site (process) monitoring of molecules in environmental technology, cleantech and food industry are as much needed as challenging. For on-site operation, such sensors have to be especially rigid and robust without the need of elaborate sample preparation, which is typically not met by current analytical laboratory methods. Detecting biomolecular interactions, surface plasmon resonance (SPR) spectroscopy is well-established and known to be the most sensitive label-free method to date [1]. However, devices currently available are designed for use in laboratory environment solely due to both their bulkiness and the elaborate adjustments of the optics necessary for excitation of propagating surface plasmon polaritons. To address these needs, we introduced a multiple-use nanoplasmonic sensor for the fast monitoring of micropollutans (in the low µg/L range) and demonstrated its application directly at the effluent of a wastewater treatment plant using the example of diclofenac [2]. This sensor technology constitutes a new and unique data source that not only facilitates process monitoring, but even further data-driven applications. After introducing the sensor technology future strategies will therefore be presented to combine real-time data on pollution with additional data describing both the supply of and demand for water of different quality. One of the ideas, for example, is to use machine-learning algorithms to predict supply and demand situations for “fit-forpurpose” water at an early stage and to provide the required quantities of water in a monitored feedback-loop.
22-Jun-2022 15:00 (30 Minutes) ICM/Hall 3
English

Maximizing the availability of smart sensors using the Netilion ecosystem

André Lemke, Endress+Hauser
Introduction The digital services of the Netilion ecosystem minimize manual work and reduce the time and cost of operating and maintaining liquid analysis measuring points for operators in water and wastewater treatment plants. Within this context, Endress+Hauser is working with various companies in the wastewater sector, for example, the Emschergenossenschaft-Lippenverband (EGLV) wastewater management company in Germany and the Municipality of Kincardine in Canada. Market requirement Many wastewater treatment plants are located in rural areas far apart from each other and are operated without being permanently staffed. This is more challenging if a malfunction occurs at an analyzer and plant operation is affected. Unscheduled service operations result in unplanned time and costs. Diagnosing and remedying faults at the measuring points are thus very complex and can only be done in some cases with the help of experts. Solution In case of an event, it is crucial for the operators to act quickly. The traditional control and asset health management systems may inform in real-time about the status of the assets. However, it is often necessary to be on the spot and when something is reported, the most important thing is missing: the instruction how to solve the problem. An edge device was used to connect it to the Endress+Hauser Netilion ecosystem via the mobile phone network. Here, encrypted measurement data and status information were sent continuously and made available in the Endress+Hauser support network. Conclusion That's what Netilion in combination with smart sensors is all about. Netilion empowers maintenance teams to be ready and effective in case of unexpected events in their plants. Netilion and the smart sensors provide the essential know-how to support the operators finding the cause and remedy of an issue. With the smart sensors, the operators enjoy a connected solution. Like this, the operators can act faster in an unexpected event and the availability of the smart sensors can be maximized and the plant performance can be kept at the highest level.
22-Jun-2022 15:30 (30 Minutes) ICM/Hall 3
English

Portable and in-situ instruments for rapid quantification of Escherichia coli in surface waters – Operation and validation of the Fluidion ALERT Technologies

Franziska Knoche, KompetenzZentrum Wasser Berlin
Online monitoring of bacteria in surface waters remains a challenging task. While several rapid, automated methods show promise, a thorough understanding of the relationship between existing laboratory methods (e.g., DIN EN ISO 9308-X) and rapid methods is needed to use the rapid measurement results for environmental policy decisions, e.g., for bathing water management. In the present study, we compared measurement results obtained from three rapid, autonomous, remotely-controllable Escherichia coli (E.coli) analyzers: ALERT LAB, ALERT System V1, ALERT System V2 (manufacturer: Fluidion), against the standardized laboratory method ISO 9308-3. While sample analysis of all devices is based on similar automated real-time modified defined substrate approaches, the devices differ in the way samples are collected. For the portable ALERT LAB, samples must be manually loaded, while for the ALERT Systems samples are automatically collected in-situ through a vacuum mechanism [1]. ALERT System V2, the latest development, uses disposable measurement cartridges which significantly simplify maintenance operations compared to version V1, eliminating potential for human error. In 2020, a 7-step dilution series ranging from 50 to 10000 MPN/mL was prepared from sterilized river water spiked with filtered secondary wastewater plant effluent. To address intra- and inter-laboratory variability, 12 aliquots of each dilution were analyzed by two independent, accredited laboratories. For the ALERT LAB and ALERT System V1, 6 and 7 aliquots were analyzed, respectively. In 2021, the experiment was repeated for the ALERT System V2, using only one reference laboratory and 7 aliquots. The device- and laboratory-specific precision and the device bias vs. the laboratory results were calculated. The ALERT LAB had a comparable precision (sd = 0.08 - 0.21 log10) to the two laboratories, and an overestimation bias of 0.12 log10 units. For the ALERT System V1, similar results were obtained but precision was degraded for lower concentrations (sd = 0.45 - 0.71 log10), an artefact of the complex maintenance procedure. Results of the ALERT System V2 show significantly improved precision at lower concentrations (sd = 0.12 - 0.17 log10), while at higher concentrations the measured precision was better than that of the laboratory (0.03 log10 vs. 0.11 log10). The ALERT System V2 shows good linearity (R2 = 0.9936). An observed bias of 0.28 log10 units could be removed by a single-point correction, resulting in good agreement over the full concentration range. Our results imply that fully-automated ALERT technology is a suitable equivalent to the reference laboratory method and a good candidate for supporting environmental decision-making.
22-Jun-2022 16:00 (30 Minutes) ICM/Hall 3
English

Cloud-based early warning system for algae monitoring in surface water

Andreas Auernhammer, TU München
A cloud based early warning system for algae monitoring is being developed in cooperation with A.U.G. and Hydroisotop GmbH within the scope of an AIF-ZIM project, which will be used to monitor surface water. Cyanobacteria possess ecophysiological strategies that allow them to use anthropogenic changes such as eutrophication of water bodies or climate change for their own advantage. Increased water temperatures, reduced pH values and overfertilization of water bodies can have a positive effect on their growth rate and lead to an excessive reproduction of these organisms. A bloom of algae on the water’s surface creates a cloudy underwater environment which has a detrimental effect on aquatic macrophytes and living organisms. With the exponential growth spurt of cyanobacteria, the amount of secondary metabolites produced, such as cyanotoxins, also increases. Dogs have been known to die after bathing in surface water due to cyanotoxins. An early warning system could provide realtime local information about the condition of a water body as well as increase safety. A.U.G.'s TRITON water sensor system consists of two main components (Figure 1). An optical sensor module provides UV-VIS absorption spectral analysis in the range of 200 to 850 nm. The second probe can determine pH, temperature, conductivity, TDS and TSS, turbidity and dissolved oxygen. The online monitoring system records these parameters in parallel and in real time. Predictive models for excessive growth of cyanobacteria are created via artificial intelligence. For this purpose, the sensor system continuously measures in surface water. The collected data is transferred to a cloud-based data management system and analyzed in real time. The physical sensor system is combined with a biosensor analysis system, which detects cyanotoxins, such as microcystin, anatoxin or saxitoxin, in an automated manner (Figure 2). The analysis principle is based on a flow-based chemiluminescence microarray immunoassay. For the cyanotoxins, a regenerative indirect competitive microarray immunoassay is applied, which can simultaneously quantify different cyanotoxins within 7 minutes. For cyanotoxin monitoring, the biosensor analysis system is combined with automated sample preparation and enrichment steps for free and intracellular toxins. Parameters that can be easily monitored are used for a prediction model and compared with learning data and selective biosensor data. This is important so that the prediction model can be continuously improved and eventually the target variables of algae growth and toxin formation can be predicted with a high degree of accuracy. Such an early warning system could allow authorities to assess the risk of surface waters on a daily basis, which is important for safe drinking water and recreational water.
22-Jun-2022 16:30 (30 Minutes) ICM/Hall 3